World Health Organization. Global tuberculosis report 2021. Geneva: World Health Organization; 2021. https://www.who.int/teams/global-tuberculosis-programme/data.
Bussi C, Gutierrez MG. Mycobacterium tuberculosis infection of host cells in space and time. FEMS Microbiol Rev. 2019;43(4):341–61.
Article
CAS
PubMed
PubMed Central
Google Scholar
Huang H, Ding N, Yang T, Li C, Jia X, Wang G, et al. Cross-sectional Whole-genome sequencing and epidemiological study of multidrug-resistant Mycobacterium tuberculosis in China. Clin Infect Dis. 2019;69(3):405–13.
Article
CAS
PubMed
Google Scholar
Tusun D, Abulimiti M, Mamuti X, Liu Z, Xu D, Li G, et al. The epidemiological characteristics of pulmonary tuberculosis—Kashgar Prefecture, Xinjiang Uygur Autonomous Region, China, 2011–2020. China CDC Wkly. 2021;3(26):557–61.
Article
PubMed
PubMed Central
Google Scholar
Lv L, Li C, Zhang X, Ding N, Cao T, Jia X, et al. RNA Profiling analysis of the serum exosomes derived from patients with active and latent Mycobacterium tuberculosis infection. Front Microbiol. 2017;8:1051.
Article
PubMed
PubMed Central
Google Scholar
Zhang G, Zhang L, Zhang M, Pan L, Wang F, Huang J, et al. Screening and assessing 11 Mycobacterium tuberculosis proteins as potential serodiagnostical markers for discriminating TB patients from BCG vaccinees. Genom Proteom Bioinf. 2009;7(3):107–15.
Article
CAS
Google Scholar
Campos LC, Rocha MV, Willers DM, Silva DR. Characteristics of patients with smear-negative pulmonary tuberculosis (TB) in a Region with High TB and HIV Prevalence. PLoS ONE. 2016;11(1): e0147933.
Article
PubMed
PubMed Central
CAS
Google Scholar
Steingart KR, Ng V, Henry M, Hopewell PC, Ramsay A, Cunningham J, et al. Sputum processing methods to improve the sensitivity of smear microscopy for tuberculosis: a systematic review. Lancet Infect Dis. 2006;6(10):664–74.
Article
PubMed
Google Scholar
Chakaya J, Khan M, Ntoumi F, Aklillu E, Fatima R, Mwaba P, et al. Global tuberculosis report 2020—reflections on the global TB burden, treatment and prevention efforts. Int J Infect Dis. 2021;113:S7.
Article
CAS
PubMed
PubMed Central
Google Scholar
Dorman SE, Schumacher SG, Alland D, Nabeta P, Armstrong DT, King B, et al. Xpert MTB/RIF ultra for detection of Mycobacterium tuberculosis and rifampicin resistance: a prospective multicentre diagnostic accuracy study. Lancet Infect Dis. 2018;18(1):76–84.
Article
CAS
PubMed
PubMed Central
Google Scholar
Getahun H, Harrington M, O’Brien R, Nunn P. Diagnosis of smear-negative pulmonary tuberculosis in people with HIV infection or AIDS in resource-constrained settings: informing urgent policy changes. Lancet. 2007;369(9578):2042–9.
Article
PubMed
Google Scholar
Boehme CC, Nabeta P, Hillemann D, Nicol MP, Shenai S, Krapp F, et al. Rapid molecular detection of tuberculosis and rifampin resistance. N Engl J Med. 2010;363(11):1005–15.
Article
CAS
PubMed
PubMed Central
Google Scholar
Olivier M, Asmis R, Hawkins GA, Howard TD, Cox LA. The need for multi-omics biomarker signatures in precision medicine. Int J Mol Sci. 2019;20(19):4781.
Article
CAS
PubMed Central
Google Scholar
Wang E, Cho WCS, Wong SCC, Liu S. Disease biomarkers for precision medicine: challenges and future opportunities. Genom Proteom Bioinf. 2017;15(2):57–8.
Article
Google Scholar
Liu L, Wu J, Shi M, Wang F, Lu H, Liu J et al. New metabolic alterations and predictive marker pipecolic acid in sera for esophageal squamous cell carcinoma. Genom Proteom Bioinf. 2022.
Li Y, Chen L. Big biological data: challenges and opportunities. Genom Proteom Bioinf. 2014;12(5):187–9.
Article
Google Scholar
German JB, Bauman DE, Burrin DG, Failla ML, Freake HC, King JC, et al. Metabolomics in the opening decade of the 21st century: building the roads to individualized health. J Nutr. 2004;134(10):2729–32.
Article
CAS
PubMed
Google Scholar
Deng J, Liu L, Yang Q, Wei C, Zhang H, Xin H, et al. Urinary metabolomic analysis to identify potential markers for the diagnosis of tuberculosis and latent tuberculosis. Arch Biochem Biophys. 2021;704: 108876.
Article
CAS
PubMed
Google Scholar
Huang H, Shi LY, Wei LL, Han YS, Yi WJ, Pan ZW, et al. Plasma metabolites Xanthine, 4-Pyridoxate, and d-glutamic acid as novel potential biomarkers for pulmonary tuberculosis. Clin Chim Acta. 2019;498:135–42.
Article
CAS
PubMed
Google Scholar
Sun L, Li JQ, Ren N, Qi H, Dong F, Xiao J, et al. Utility of novel plasma metabolic markers in the diagnosis of pediatric tuberculosis: a classification and regression tree analysis approach. J Proteome Res. 2016;15(9):3118–25.
Article
CAS
PubMed
Google Scholar
Pang Z, Chong J, Zhou G, de Lima Morais DA, Chang L, Barrette M, et al. MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights. Nucleic Acids Res. 2021;49(W1):W388–96.
Article
CAS
PubMed
PubMed Central
Google Scholar
Pan R, Yang T, Cao J, Lu K, Zhang ZC, et al. Missing data imputation by K nearest neighbours based on grey relational structure and mutual information. Appl Intell. 2015;43:614–32.
Article
Google Scholar
Abdi H, Williams LJ. Principal component analysis. Wiley Interdiscip Rev Comput Stat. 2010;2:433–59.
Article
Google Scholar
Bewick V, Cheek L, Ball J. Statistics review 13: receiver operating characteristic curves. Crit Care. 2004;8:508.
Article
PubMed
PubMed Central
Google Scholar
Breiman L. Random forests. Mach Learn. 2001;45:5–32.
Article
Google Scholar
Abadi M, Agarwal A, Barham P, Brevdo E, Chen Z, Citro C, et al. Tensor flow: large-scale machine learning on heterogeneous systems. 2015. Available online at: tensorflow.org.
Palaci M, Dietze R, Hadad DJ, Ribeiro FK, Peres RL, Vinhas SA, et al. Cavitary disease and quantitative sputum bacillary load in cases of pulmonary tuberculosis. J Clin Microbiol. 2007;45(12):4064–6.
Article
PubMed
PubMed Central
Google Scholar
Kang W, Wu M, Yang K, Ertai A, Wu S, Geng S, et al. Factors associated with negative T-SPOT.TB results among smear-negative tuberculosis patients in China. Sci Rep. 2018;8(1):4236.
Article
PubMed
PubMed Central
CAS
Google Scholar
Nakao M, Muramatsu H, Arakawa S, Sakai Y, Suzuki Y, Fujita K, et al. Immunonutritional status and pulmonary cavitation in patients with tuberculosis: a revisit with an assessment of neutrophil/lymphocyte ratio. Respir Investig. 2019;57(1):60–6.
Article
PubMed
Google Scholar
Berhane M, Melku M, Amsalu A, Enawgaw B, Getaneh Z, Asrie F. The role of neutrophil to lymphocyte count ratio in the differential diagnosis of pulmonary tuberculosis and bacterial community-acquired pneumonia: a cross-sectional study at Ayder and Mekelle Hospitals, Ethiopia. Clin Lab 2019, 65(4).
Shvets OM, Shevchenko OS, Todoriko LD, Shevchenko RS, Yakimets VV, Choporova OI, et al. Carbohydrate and lipid metabolic profiles of tuberculosis patients with bilateral pulmonary lesions and mycobacteria excretion. Wiad Lek. 2020;73(7):1373–6.
Article
PubMed
Google Scholar
Zhang P, Zhang W, Lang Y, Qu Y, Chen J, Cui L. 1H nuclear magnetic resonance-based metabolic profiling of cerebrospinal fluid to identify metabolic features and markers for tuberculosis meningitis. Infect Genet Evol. 2019;68:253–64.
Article
CAS
PubMed
Google Scholar
Collins JM, Walker DI, Jones DP, Tukvadze N, Liu KH, Tran VT, et al. High-resolution plasma metabolomics analysis to detect Mycobacterium tuberculosis-associated metabolites that distinguish active pulmonary tuberculosis in humans. PLoS ONE. 2018;13(10): e0205398.
Article
PubMed
PubMed Central
CAS
Google Scholar
Frediani JK, Jones DP, Tukvadze N, Uppal K, Sanikidze E, Kipiani M, et al. Plasma metabolomics in human pulmonary tuberculosis disease: a pilot study. PLoS ONE. 2014;9(10): e108854.
Article
PubMed
PubMed Central
CAS
Google Scholar
Zhou A, Ni J, Xu Z, Wang Y, Lu S, Sha W, et al. Application of (1)h NMR spectroscopy-based metabolomics to sera of tuberculosis patients. J Proteome Res. 2013;12(10):4642–9.
Article
CAS
PubMed
Google Scholar
Kim E, Kang YG, Kim YJ, Lee TR, Yoo BC, Jo M, et al. Dehydroabietic acid suppresses inflammatory response via suppression of Src-, Syk-, and TAK1-mediated pathways. Int J Mol Sci. 2019;20(7):1593.
Article
CAS
PubMed Central
Google Scholar
Kartha S, Yan L, Ita ME, Amirshaghaghi A, Luo L, Wei Y, et al. Phospholipase A2 inhibitor-loaded phospholipid micelles abolish neuropathic pain. ACS Nano. 2020;14(7):8103–15.
Article
CAS
PubMed
PubMed Central
Google Scholar
Jankute M, Cox JA, Harrison J, Besra GS. Assembly of the mycobacterial cell Wall. Annu Rev Microbiol. 2015;69:405–23.
Article
CAS
PubMed
Google Scholar
Srivastava S, Chaudhary S, Thukral L, Shi C, Gupta RD, Gupta R, et al. Unsaturated lipid assimilation by mycobacteria requires auxiliary cis-trans enoyl CoA isomerase. Chem Biol. 2015;22(12):1577–87.
Article
CAS
PubMed
Google Scholar
Mu J, Yang Y, Chen J, Cheng K, Li Q, Wei Y, et al. Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients. Biochem Biophys Res Commun. 2015;466(4):689–95.
Article
CAS
PubMed
Google Scholar
Goto T, Lee JY, Teraminami A, Kim YI, Hirai S, Uemura T, et al. Activation of peroxisome proliferator-activated receptor-alpha stimulates both differentiation and fatty acid oxidation in adipocytes. J Lipid Res. 2011;52(5):873–84.
Article
CAS
PubMed
PubMed Central
Google Scholar
Andres Contreras G, De Koster J, de Souza J, Laguna J, Mavangira V, Nelli RK, et al. Lipolysis modulates the biosynthesis of inflammatory lipid mediators derived from linoleic acid in adipose tissue of periparturient dairy cows. J Dairy Sci. 2020;103(2):1944–55.
Article
CAS
PubMed
Google Scholar
Armstrong MM, Diaz G, Kenyon V, Holman TR. Inhibitory and mechanistic investigations of oxo-lipids with human lipoxygenase isozymes. Bioorg Med Chem. 2014;22(15):4293–7.
Article
CAS
PubMed
PubMed Central
Google Scholar
Mattmiller SA, Carlson BA, Gandy JC, Sordillo LM. Reduced macrophage selenoprotein expression alters oxidized lipid metabolite biosynthesis from arachidonic and linoleic acid. J Nutr Biochem. 2014;25(6):647–54.
Article
CAS
PubMed
Google Scholar
Nienaber A, Baumgartner J, Dolman RC, Ozturk M, Zandberg L, Hayford FEA, et al. Omega-3 fatty acid and iron supplementation alone, but not in combination, lower inflammation and anemia of infection in Mycobacterium tuberculosis-infected mice. Nutrients. 2020;12(9):2897.
Article
CAS
PubMed Central
Google Scholar
Orlowski M, Meister A. The gamma-glutamyl cycle: a possible transport system for amino acids. Proc Natl Acad Sci U S A. 1970;67(3):1248–55.
Article
CAS
PubMed
PubMed Central
Google Scholar
Gamarra Y, Santiago FC, Molina-Lopez J, Castano J, Herrera-Quintana L, Dominguez A, et al. Pyroglutamic acidosis by glutathione regeneration blockage in critical patients with septic shock. Crit Care. 2019;23(1):162.
Article
PubMed
PubMed Central
Google Scholar
Balazy M, Kaminski PM, Mao K, Tan J, Wolin MS. S-Nitroglutathione, a product of the reaction between peroxynitrite and glutathione that generates nitric oxide. J Biol Chem. 1998;273(48):32009–15.
Article
CAS
PubMed
Google Scholar
Ly J, Lagman M, Saing T, Singh MK, Tudela EV, Morris D, et al. Liposomal glutathione supplementation restores TH1 cytokine response to Mycobacterium tuberculosis infection in HIV-infected individuals. J Interferon Cytokine Res. 2015;35(11):875–87.
Article
CAS
PubMed
PubMed Central
Google Scholar
He R, Zeng LF, He Y, Wu L, Gunawan AM, Zhang ZY. Organocatalytic multicomponent reaction for the acquisition of a selective inhibitor of mPTPB, a virulence factor of tuberculosis. Chem Commun (Camb). 2013;49(20):2064–6.
Article
CAS
Google Scholar
Fu YR, Yi ZJ, Guan SZ, Zhang SY, Li M. Proteomic analysis of sputum in patients with active pulmonary tuberculosis. Clin Microbiol Infect. 2012;18(12):1241–7.
Article
CAS
PubMed
Google Scholar
Zhang J, Han X, Gao C, Xing Y, Qi Z, Liu R, et al. 5-Hydroxymethylome in circulating cell-free DNA as a potential biomarker for non-small-cell lung Cancer. Genom Proteom Bioinf. 2018;16(3):187–99.
Article
CAS
Google Scholar
Riniker S, Wang Y, Jenkins JL, Landrum GA. Using information from historical high-throughput screens to predict active compounds. J Chem Inf Model. 2014;54(7):1880–91.
Article
CAS
PubMed
Google Scholar
Wang J, Xie X, Shi J, He W, Chen Q, Chen L, et al. Denoising autoencoder, a deep learning algorithm, aids the identification of a novel molecular signature of lung adenocarcinoma. Genom Proteom Bioinf. 2020;18(4):468–80.
Article
Google Scholar
Akkasi A, Moens MF. Causal relationship extraction from biomedical text using deep neural models: a comprehensive survey. J Biomed Inform. 2021;119: 103820.
Article
PubMed
Google Scholar
Yang Q, Chen Q, Zhang M, Cai Y, Yang F, Zhang J, et al. Identification of eight-protein biosignature for diagnosis of tuberculosis. Thorax. 2020;75(7):576–83.
Article
PubMed
Google Scholar
Huang MW, Chen CW, Lin WC, Ke SW, Tsai CF. SVM and SVM ensembles in breast cancer prediction. PLoS ONE. 2017;12(1): e0161501.
Article
PubMed
PubMed Central
CAS
Google Scholar
Er O, Temurtas F, Tanrikulu AC. Tuberculosis disease diagnosis using artificial neural networks. J Med Syst. 2010;34(3):299–302.
Article
PubMed
Google Scholar
de Souza Filho JBO, de Seixas JM, Galliez R, de Braganca Pereira B, de Mello FCQ, Dos Santos AM, et al. A screening system for smear-negative pulmonary tuberculosis using artificial neural networks. Int J Infect Dis. 2016;49:33–9.
Article
Google Scholar
Haug K, Cochrane K, Nainala VC, Williams M, Chang J, Jayaseelan KV, et al. MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Res. 2020;48(D1):D440–4.
CAS
PubMed
Google Scholar